Typical object recognition is the task of finding a given object in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects is seen from different points-of-view and varying levels of scale, size, and appearance.
Recently, with the spread of the three-dimensional (3D) scanners, the data collected about objects comes in the form of 3D models. For example, in architecture and construction, 3D scanners are directly used for measuring and visualizing buildings through the generation of a set of data points in a coordinate system known as a point cloud. In the medical field, the CT, MRI, or Micro-CT scanners produce a set of two-dimensional (2D) slices which are then stacked together to produce a 3D representation. In modern augmented reality and gaming fields, laser scanners are used in real-time to generate 3D models for real objects that are integrated somehow with a virtual environment presented on a wearable display or glasses connected to a computer.
In fact, there is a need for a universal method and a technique that enables the recognition of objects in 3D models to serve the current and future applications of various medical, engineering, industrial, gaming, and entertainment fields.